Corresponding to the following paper:
Vahid Garousi, Ehsan Abbasi, Roshanak Farhoodi, Richard Bauer, Allan Shea, “Engineering software systems for improving the operational efficiency of oil pipeline networks and decreasing their carbon footprint”, A video presentation for the Second International Workshop on Software Research and Climate Change, Cape Town, South Africa, May 3, 2010, part of the ICSE 2010
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Engineering software systems for improving the operational efficiency of oil pipeline networks and decreasing their carbon footprint
1. 1Vahid Garousi, 2006-2012
Engineering Software Systems for Improving the
Operational Efficiency of Oil Pipeline Networks
and Decreasing their Carbon Footprint
Vahid Garousi, Ehsan Abbasi,
Roshanak Farhoodi
Software Quality Engineering
Research Group (SoftQual)
www.softqual.ucalgary.ca
Department of Electrical and
Computer Engineering
University of Calgary, Canada
A video presentation for the
Second International Workshop on Software
Research and Climate Change (WSRCC 2010)
Cape Town, South Africa
May 3, 2010, co-located with ICSE 2010
Richard Bauer, Allan Shea
Pembina Pipelines Corporation
www.pembina.com
Calgary, Canada
Thanks to funding and support from:
2. 2Vahid Garousi, 2006-2012
Lots of Carbon Footprint to Transport Oil Products
(Public) data from one of our
industrial partners, Pembina
Pipelines (www.pembina.com)...
In year 2008, Pembina Pipelines
spent about $18.11 Million Canadian
dollars on electricity costs
almost all (98%) of which were spent on
pumping.
Average regional energy prices for
electricity in Alberta: 7.99¢/kWh
This would yield about 226.5 MWh
for our industrial partner in year
2008.
Assuming that only coal is used for
electricity generation
using an existing benchmark for calculation
of carbon footprint in electricity generation
this would lead to 182,460 tons of CO2
emissions annually.
Provide the energy for
Pembina Pipeline Corporation, 2008 Annual Report (public information)
http://www.pembina.com/webcms.nsf/AllDoc/0A7E6DFB88C344B387257570007A5C3B/
$File/2008AnnualReport.pdf
3. 3Vahid Garousi, 2006-2012
Lots of Carbon Footprint to Transport Oil Products
Our manual analysis of the SCADA log
data have shown that a lot of energy is
being lost due to the use of:
ad-hoc operational decisions
based on operators’ experience
rule of the thumb, and “gut feelings”
Valves are used quite often (just like
pressing the Brake pedal in your car!)
We are in the process of quantitatively
measuring the % of energy lost due to
this.
4. 4Vahid Garousi, 2006-2012
The work reported in this talk is conducted as a part of a R&D
project in Alberta with the collaboration of academia and the
petroleum industry.
Funded by the Alberta Ingenuity (now, “Alberta Innovates”)
Project title:
Engineering Intelligent Software Systems for Improving the
Operational Efficiency of Oil Pipeline Networks
Our focus is on:
Developing effective software
systems to enable interoperability
with existing systems, GIS, SCADA
software, databases, etc.
Developing optimization algorithms
(MILP, GA, etc.)
More info:
http://www.ucalgary.ca/~vgarousi/proje
ct-sw-energy.html
Project Context
A snapshot of our prototype tool (details coming)
5. 5Vahid Garousi, 2006-2012
Motivations
What is the need for these software systems?
There are 100,000+ KM of
oil pipelines only in the
North America
These systems are fully
controlled by software-
intensive control systems
Ironically, most pipeline
operators STILL use error-
pone and human-intensive
approaches, e.g.
copy/pasting data and
calculating the operational
settings in Excel
[as per our meetings with 10+
industrial leaders in the area]
The pipeline network map of one North American operator
Source: http://www.transcanada.com/investor/annual_reports/2008/progress_report/assets
6. 6Vahid Garousi, 2006-2012
Motivations
Although various software systems
are successfully being used in
these systems, e.g.,
SCADA (control and monitoring systems)
Pipeline hydraulics software
But most pipeline operators
complain about the lack of effective
software systems for optimum pump
operations
“Several efforts [contracts] to build
optimization software to optimize [reduce]
energy consumption of pumps have
failed!. One such system was using GAs.”
[as per our meetings with 10+ industrial
leaders in the area]
Most of the operational decisions
are still being made in ad-hoc
fashions based on operators’
experience, rule of the thumb, and
“gut feelings”
14. 14Vahid Garousi, 2006-2012
Some Results from our Optimization
Engine
From http://tinyurl.com/pembina2009report-pdf
Cost ($)
0
1,000
2,000
3,000
4,000
5,000
6,000
Taylor
W
illow
Flats
M
cLeod
PrinceGeorge
Australian
LacLaHache
TOTAL
Pump Stations
Electricitycharge($)perHour
Results from Lingo
Actual operation (SCADA)
Carbon Footprint
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
Taylor
W
illow
Flats
M
cLeod
Prince
George
Australian
LacLa
Hache
TOTAL
Pump Stations
CO2generated(KG/hour)
Results from Lingo
Actual operation (SCADA)
Editor's Notes
The optimization method that we have developed enables a win-win situation for both the environment and pipeline companies by, firstly, reducing the carbon footprint due to enormous electricity usage of pumping operations. Secondly, our method enables pipeline companies to reduce their pumping costs. Data from one of our industrial partners, Pembina Pipelines (www.pembina.com), an oil pipeline operator in Western Canada, can provide a perspective on how enormous the above measures can be.
In year 2008, Pembina Pipelines spent about $18.11 Million Canadian dollars on electricity costs, almost all of which were spent on pumping [4].
To reversely calculate the amount of energy which has led to the above pumping cost, and using the average regional energy prices for electricity in Alberta (7.99¢/kWh) [5], one would get about 226.5 MWH for our industrial partner. We can then calculate the carbon footprint (emissions) produced to generate the above amount of electricity. Assuming that only coal is used for electricity generation, using an example benchmark for calculation of carbon footprint in electricity generation [6], this would lead to 182,460 tons of CO2 emissions annually.